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'freeze_bn' not recognized about keras-retinanet HOT 5 CLOSED

fizyr avatar fizyr commented on August 27, 2024
'freeze_bn' not recognized

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Comments (5)

mhwilder avatar mhwilder commented on August 27, 2024 1

Thanks for the update and the quick response to this issue. I was able to get it to work by cloning keras-resnet repo and installing it (which looks to be what you suggest in the updated readme). Seems to be working now.

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hgaiser avatar hgaiser commented on August 27, 2024

I'm guessing you don't have the latest version (master even) of keras-resnet installed. I'll update the README.md with a guide on how to install keras-retinanet.

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mhwilder avatar mhwilder commented on August 27, 2024

Thanks. When I ran the setup script, this is what was installed:

Installed /usr/local/lib/python2.7/dist-packages/keras_retinanet-0.0.1-py2.7.egg
Processing dependencies for keras-retinanet==0.0.1
Searching for keras-resnet
Reading https://pypi.python.org/simple/keras-resnet/
Downloading https://pypi.python.org/packages/30/19/a348c06440276c575a578ae41a953e81ba7a643bb548afda19fad5c89775/keras-resnet-0.0.8.tar.gz#md5=07f8e0f6462df78a4662c77f0da02f9d
Best match: keras-resnet 0.0.8
Processing keras-resnet-0.0.8.tar.gz
Writing /tmp/easy_install-EjGzMF/keras-resnet-0.0.8/setup.cfg
Running keras-resnet-0.0.8/setup.py -q bdist_egg --dist-dir /tmp/easy_install-EjGzMF/keras-resnet-0.0.8/egg-dist-tmp-bYQGtV
zip_safe flag not set; analyzing archive contents...
Moving keras_resnet-0.0.8-py2.7.egg to /usr/local/lib/python2.7/dist-packages
Adding keras-resnet 0.0.8 to easy-install.pth file

Installed /usr/local/lib/python2.7/dist-packages/keras_resnet-0.0.8-py2.7.egg

Does that look like an older version?

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jwnsu avatar jwnsu commented on August 27, 2024

check closed issue for solution: #16, which resolved same issue for me (reinstall keras-resnet from a fix branch: "pip install git+https://github.com/delftrobotics-forks/keras-resnet@bn-freeze").

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hgaiser avatar hgaiser commented on August 27, 2024

This commit should address this issue. Feedback on this guide is welcome, I couldn't test it fully due to that tensorflow-gpu on pypi seems to use CUDA 8 while I have CUDA 9 installed.

If it doesn't work and you need to take extra steps, I'd be happy to hear them.

Also if this resolves your issue, please close this issue.

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